The toolbox contains four time-domain methods for identifying IO model structures (REF ): 1) linear regression, 2) pseudo-linear regression, 3) gradient-based search, and 4) instrumental variable method. These methods are based on [1]}, [2]}, [3]}. Linear regression is applicable for the ARX model set and the model estimate is obtained by executing |lpvarx|. For the |lpvarx| method, regularization is included by solving a Tikhonov regression problem, where various weighting matrices can automatically be tuned using generalised cross-validation [4]} or marginal likelihood optimization [5]}. These options can be selected using the option set |lpvarxOptions|. The pseudo-linear regression algorithm is executed for the ARMAX, OE, and BJ model sets by calling |lpvarmax|, |lpvoe|, and |lpvbj|, respectively. The gradient-based search is applicable for all afore-mentioned model types and is executed by calling |lpvpolyest|. The instrumental variable method is applied by the command |lpviv|. At the moment, this function is available for model structures with a single input and a single output (SISO), and will be extended to the general case in a later release.
